Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An ontology-based BIM Expert System for temporal and spatial construction planning
The effective realization of building construction is closely linked to the construction schedules that, if poorly designed, result in congested site areas, accidents and decline of productivity. In the past decade, many research efforts have been spent in BIM which represents the process of preparation and use of a computer-generated Building Information Model (BIM) even if an effective model to assist construction scheduling is still missing. This PhD thesis proposes an Expert-System able to identify the shortest completion sequence of a given Building Information Model, considering the on-site temporal-space allocation of workspaces. It is supported by an ontology-based system architecture integrated with a rule-based artificial intelligence. Four integrated ontologies, to formally represent construction site entities, constitute the system’s Knowledge-Base (KB): (1) scheduling ontology that maps the necessary components to specify the scheduling task (2) space ontology that contains workspaces requirements in terms of geometries, locations and interactions (3) products ontology that describes geometrical and topological information of the building objects (4) time ontology that describes temporal properties of site entities in their evolution across time. Such a KB was rendered into a Protégé’s script (ontology editing environment) in order to convert it in machine-readable language (i.e., Web Ontology Language –OWL). Furthermore, four automated Reasoning Mechanisms –scripts- were incorporated in the model architecture: (i) an algorithm to define the on-site workspaces configuration pattern, (ii) an algorithm to automatically model workspaces geometries, (iii) a workspaces conflicts checking process and (iv) a rule-engine to deduce the shortest construction sequence and solve the identified conflicts manipulating the KB itself. A validation test was conducted on a BIM-based project of an industrial building composed of 98 building items and 611 workspaces, allocated by means of (i) and modelled with (ii). A construction sequence of 36 construction days was suggested by the system. Moreover, 118 workspaces conflicts were identified (iii) and automatically solved by using the planning rules included in the rule-engine as it was visually verified simulating the sequence itself within a 4D-BIM environment. This prototype can be considered a precursor model in developing BIM-based intelligent systems architectures for spatial construction planning.
An ontology-based BIM Expert System for temporal and spatial construction planning
The effective realization of building construction is closely linked to the construction schedules that, if poorly designed, result in congested site areas, accidents and decline of productivity. In the past decade, many research efforts have been spent in BIM which represents the process of preparation and use of a computer-generated Building Information Model (BIM) even if an effective model to assist construction scheduling is still missing. This PhD thesis proposes an Expert-System able to identify the shortest completion sequence of a given Building Information Model, considering the on-site temporal-space allocation of workspaces. It is supported by an ontology-based system architecture integrated with a rule-based artificial intelligence. Four integrated ontologies, to formally represent construction site entities, constitute the system’s Knowledge-Base (KB): (1) scheduling ontology that maps the necessary components to specify the scheduling task (2) space ontology that contains workspaces requirements in terms of geometries, locations and interactions (3) products ontology that describes geometrical and topological information of the building objects (4) time ontology that describes temporal properties of site entities in their evolution across time. Such a KB was rendered into a Protégé’s script (ontology editing environment) in order to convert it in machine-readable language (i.e., Web Ontology Language –OWL). Furthermore, four automated Reasoning Mechanisms –scripts- were incorporated in the model architecture: (i) an algorithm to define the on-site workspaces configuration pattern, (ii) an algorithm to automatically model workspaces geometries, (iii) a workspaces conflicts checking process and (iv) a rule-engine to deduce the shortest construction sequence and solve the identified conflicts manipulating the KB itself. A validation test was conducted on a BIM-based project of an industrial building composed of 98 building items and 611 workspaces, allocated by means of (i) and modelled with (ii). A construction sequence of 36 construction days was suggested by the system. Moreover, 118 workspaces conflicts were identified (iii) and automatically solved by using the planning rules included in the rule-engine as it was visually verified simulating the sequence itself within a 4D-BIM environment. This prototype can be considered a precursor model in developing BIM-based intelligent systems architectures for spatial construction planning.
An ontology-based BIM Expert System for temporal and spatial construction planning
Ein BIM Ontologie-basiertes Expertensystem für räumliche und zeitliche Programmierungen von Bauten
Getuli, Vito (Autor:in) / Universitätsbibliothek Braunschweig (Gastgebende Institution) / Geier, Martin (Akademische:r Betreuer:in)
2019
Sonstige
Elektronische Ressource
Englisch
An ontology-based BIM Expert System for temporal and spatial construction planning
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An ontology-based BIM Expert System for temporal and spatial construction planning
| UB Braunschweig | 2018